Haznadar M, Cai Q, Krausz KW, Bowman ED, Margono E, Noro R, Thompson MD, Mathe EA, Munro HM, Steinwandel MD, Gonzalez FJ, Blot WJ, Harris CC. Urinary Metabolite Risk Biomarkers of Lung Cancer: A Prospective Cohort Study. Cancer Epidemiol Biomarkers Prev. 2016 Jun;25(6):978-86. doi: 10.1158/1055-9965.EPI-15-1191. We previously conducted a first-of-its-kind unbiased metabolomics study to determine whether lung cancer patients can be distinguished from healthy controls using MS-derived urine metabolic profiles, establishing robust biomarkers of risk, diagnosis and prognosis of cancer (Mathe, 2014). Initially, Random Forests analysis was utilized for classification of lung cancer patients compared to non-diseased controls, resulting in 78.1% classification accuracy (True Positive Rate [TPR] = 76.5%, False Positive Rate [FPR] = 18.4%), by employing top predictive signals. Four metabolites contributed most significantly to the classifications, independent of race, gender and smoking status: N-acetylneuraminic acid (NANA;) cortisol sulfate (CS); creatine riboside (CR), novel metabolite identified in this study; and 561+, an unidentified metabolite with a mass/charge ratio of 561.3432+, a glucuronidated compound. We have conducted extensive validation methods to confirm the identity of novel creatine riboside, including ultraperformance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS), 2D NMR, and, recently, its chemical synthesis. We were successful in obtaining a creatine riboside synthetic standard that corresponds to creatine riboside detected in biofluids and tissue. Two of four metabolites, CR and NANA, are linked to deregulated tumor metabolism. To evaluate the utility of urine metabolomics markers in prediagnostic samples, we designed a nested case-control study within the prospective Southern Community Cohort Study (SCCS) that comprises 50% of African-American subjects, a traditionally understudied population, wherein both, European- and African-American populations come from similar socio-economic backgrounds minimizing it as a potential confounder. High levels of two metabolites, CR and NANA, previously linked to deregulated tumor-metabolism, were associated with increased lung cancer risk (CR: ORadjusted =1.9; 95% CI, 1.0-3.6; P =0.4; NANA: ORadjusted =2.0; 95% CI, 1.1-3.6; P =0.02). These associations were stronger in European-Americans and remained significant even when individuals diagnosed within 2 years of cohort enrollment ware removed from the analysis in order to minimize incidental lung cancer. Finally, to evaluate the ability of CR and NANA alone and in combination to classify lung cancer, Receiver Operating Characteristic (ROC) analysis was performed, leading to the findings of a significant improvement in the Area Under the Curve (AUC) after the addition of CR and NANA to the model containing established risk factors (smoking status, pack years, age, BMI, income and education levels, previous history of COPD, and family history of lung cancer), from 0.84 to 0.90, respectively; P = 0.002, with a selected cut-off point leading to a correct classification of 84% of subjects (Positive Predictive Value (PPV) = 75%; Negative Predictive Value (NPV) = 89%).